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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<h3><a id="index_p" name="index_p"></a>- p -</h3><ul>
<li>p&#160;:&#160;<a class="el" href="structshark_1_1_qp_mc_box_decomp_1_1_variable.html#ad49781ffc9b6ea569bd20eff24baaa4d">shark::QpMcBoxDecomp&lt; Matrix &gt;::Variable</a>, <a class="el" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#ab28a742507fae39e644ac56ae9db49e1">shark::QpMcSimplexDecomp&lt; Matrix &gt;::Variable</a></li>
<li>PamiToy()&#160;:&#160;<a class="el" href="classshark_1_1_pami_toy.html#a77a00e9bdae220f5b1054564835b7cf0">shark::PamiToy</a></li>
<li>parameterDerivative()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#abb90ca0c305f3ee67f0417834eb0f77a">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a2182a946b08304704794d5d6de4c5027">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a0fb9583b9a3316795085314c93499e08">shark::GaussianLayer</a></li>
<li>parameterName()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_result_table.html#acaf72de2fe5ff0bc13c8de25dc49ac3d">shark::statistics::ResultTable&lt; Parameter &gt;</a>, <a class="el" href="structshark_1_1statistics_1_1_statistics.html#aa5790b0a3c024406f404fe42274b177e">shark::statistics::Statistics&lt; Parameter &gt;</a></li>
<li>parameterValue()&#160;:&#160;<a class="el" href="classshark_1_1statistics_1_1_result_table.html#a3d24ba543fac0fb8f92026d52a17ca63">shark::statistics::ResultTable&lt; Parameter &gt;</a>, <a class="el" href="structshark_1_1statistics_1_1_statistics.html#a3f693c6f2d0e7781206e8c4b6faf5a30">shark::statistics::Statistics&lt; Parameter &gt;</a></li>
<li>parameterVector()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#a78155370989cbdd02f04050693eccac5">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_svm_trainer.html#a183757faebfc331f6733946a6ea7de2c">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_a_r_d_kernel_unconstrained.html#a81946af98e00e545233603f2c66c2cff">shark::ARDKernelUnconstrained&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_binary_layer.html#ae7503f9816f24d2cd140f167e9642958">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#ab9d2af87303f98a051ff202cd872c187">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_c_a_r_tree.html#a6e4f9312692c66350cdeca84237a89b6">shark::CARTree&lt; LabelType &gt;</a>, <a class="el" href="classshark_1_1_centroids.html#aeda09ff6d0c326df4c90eb3ebe2d214a">shark::Centroids</a>, <a class="el" href="classshark_1_1_classifier.html#aaf00d04ae93bc8a05768c6c3055fe79e">shark::Classifier&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_clustering_model.html#a82452bf00a5de777684ffc304e548cad">shark::ClusteringModel&lt; InputT, OutputT &gt;</a>, <a class="el" href="classshark_1_1_c_m_a_c_map.html#a6e01866bc989b8671047e1474cace120">shark::CMACMap</a>, <a class="el" href="classshark_1_1_concatenated_model.html#a30498e619406375917645ae64be5610e">shark::ConcatenatedModel&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_conv2_d_model.html#a65a69c4c0b9fe12db3950e04d625be7e">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_discrete_kernel.html#a7f7a56ec81071ac947ce02df48b0778c">shark::DiscreteKernel</a>, <a class="el" href="classshark_1_1_dropout_layer.html#adeea5374f92a670be86d50c3eb054afd">shark::DropoutLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_epsilon_svm_trainer.html#a631651231f0bfbe6d61c26117cdb4c6b">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#a4dbab4818dff8ee8011b94713513bf4f">shark::GaussianLayer</a>, <a class="el" href="classshark_1_1_gaussian_rbf_kernel.html#a10d28ce6e3267a9816007bd6aa5e5ed9">shark::GaussianRbfKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_task_kernel.html#aa2b81431e43f111b7ff8d3b6ea9eda58">shark::GaussianTaskKernel&lt; InputTypeT &gt;</a>, <a class="el" href="classshark_1_1_hierarchical_clustering.html#a9705432311cb424191f62237f9066238">shark::HierarchicalClustering&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_i_parameterizable.html#afaa2ba692ab64a0edbff60d7ee6794db">shark::IParameterizable&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#ae4573dfb8f348f21bc95c74eddc97b48">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#a6b91222bf74774ac83e049f95d03f6c7">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#ab9e4920082ba0a7a88a9589d82024326">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_lasso_regression.html#aa23ec16704158ce8b7f5d7f501f4429a">shark::LassoRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_l_d_a.html#a44509c51933cc29a3c069df195cb0a77">shark::LDA</a>, <a class="el" href="classshark_1_1_linear_kernel.html#ab25e1b9f9a5916695421d91067d08141">shark::LinearKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#a26fc78bc3f8a04e11b41542c3dfe3dec">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_linear_regression.html#ac1cf68783fe0cd6ecc5e7a03f2043017">shark::LinearRegression</a>, <a class="el" href="classshark_1_1_linear_s_a_g_trainer.html#aa2f194a2bf0013a85e567c3802391837">shark::LinearSAGTrainer&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_logistic_regression.html#a45c601e09b06f3b464fdc978f9d40493">shark::LogisticRegression&lt; InputVectorType &gt;</a>, <a class="el" href="classshark_1_1_model_kernel.html#aadb40dc66293ba8f4f6ea6e818f68045">shark::ModelKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_monomial_kernel.html#a8e4923483fa0fd76bf839dd363c1854f">shark::MonomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_neuron_layer.html#acbe7aff1486b54161b195c4b2501ba42">shark::NeuronLayer&lt; NeuronType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_normalized_kernel.html#a1246ed4aa52cb8ce5a2216df17f93426">shark::NormalizedKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_normalizer.html#a019f069459a4f5a83d98569cbd08980d">shark::Normalizer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_one_class_svm_trainer.html#af0e0e80c71cf974970ecc742b47a2452">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_one_versus_one_classifier.html#ab391eb00c83476a3b2de06d717849510">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_point_set_kernel.html#ad4656384d3ee3a6a5bee3466ae17a96a">shark::PointSetKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_polynomial_kernel.html#a55528a26a7ce6c6ed98bc8523cf98e5d">shark::PolynomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#afc8367c726013f74b5b5ab61dd16693a">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_product_kernel.html#a3c48a869a311ce86dcf66552f6d09e80">shark::ProductKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_r_b_f_layer.html#a5e089c9692be82ff557922798fecd588">shark::RBFLayer</a>, <a class="el" href="classshark_1_1_r_b_m.html#aef829473dfa3b3c8bce134aba6fd7420">shark::RBM&lt; VisibleLayerT, HiddenLayerT, randomT &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#aa5ceb0d72cba7461594d9dd2f6642a1a">shark::ResizeLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01_real_vector_01_4.html#a9a0674d771e229c820f0d3dfa24b38a2">shark::RFTrainer&lt; RealVector &gt;</a>, <a class="el" href="classshark_1_1_r_f_trainer_3_01unsigned_01int_01_4.html#adefc3f79dc834760239e68f7a3ad4f24">shark::RFTrainer&lt; unsigned int &gt;</a>, <a class="el" href="classshark_1_1_scaled_kernel.html#a62e229f1458a7a82f9739bedd4e5009c">shark::ScaledKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_weighted_sum_kernel.html#a7947a32a41b0bff7ac5e1f5532cccf51">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>ParameterVectorType&#160;:&#160;<a class="el" href="classshark_1_1_classifier.html#a2e36a54e9541fbc7ed0138fd91c9a6a9">shark::Classifier&lt; Model &gt;</a>, <a class="el" href="classshark_1_1_concatenated_model.html#a070d86b2c6c81efcb1b4022e50feeb18">shark::ConcatenatedModel&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_conv2_d_model.html#a1a6bf16a226df283254eed73c480b280">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_dropout_layer.html#a5afad3ac1ca85c8745900ccf74638acb">shark::DropoutLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_i_parameterizable.html#a2ad5e2e60b2b352988b41f46024d790b">shark::IParameterizable&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#a77c13e729eb7160c2ef7ed6b9313b127">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_neuron_layer.html#a134859aea3b11c60ce809eec77789860">shark::NeuronLayer&lt; NeuronType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_optimization_trainer.html#a94821f625b14c0a2110f8fe1573e04b2">shark::OptimizationTrainer&lt; Model, LabelTypeT &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#ac7cdb7122418ae31bef77d22aae75910">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#a165db648b407275a7a9b2d870757c8ff">shark::ResizeLayer&lt; VectorType &gt;</a></li>
<li>parent()&#160;:&#160;<a class="el" href="classshark_1_1_binary_tree.html#acf31280508b15cf67be7b7b4d30e41f5">shark::BinaryTree&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_c_m_a_individual.html#af679e2b6bf0519ae145cf1cd196886c9">shark::CMAIndividual&lt; FitnessType &gt;</a></li>
<li>partCovers()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator_m_d_h_o_y.html#a4e5d2c7e7348e7bdeb0b5962e7f5241a">shark::HypervolumeCalculatorMDHOY</a></li>
<li>PartlyPrecomputedMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_partly_precomputed_matrix.html#ab2069225766e15ddd81809953c940467">shark::PartlyPrecomputedMatrix&lt; Matrix &gt;</a></li>
<li>PartlyPrecomputedMatrixType&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a86c3c80eefc4b570704a0d8bbc5a0f97">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#adf916f6e4f7e0593ba14ef630f9a449d">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>PATCH()&#160;:&#160;<a class="el" href="structshark_1_1_shark_1_1_version.html#acc94927f9746196f87cc94532b9387d5">shark::Shark::Version&lt; major, minor, patch &gt;</a></li>
<li>PCA()&#160;:&#160;<a class="el" href="classshark_1_1_p_c_a.html#a439006abce1b7c09792b7c574a2d709e">shark::PCA</a></li>
<li>PCAAlgorithm&#160;:&#160;<a class="el" href="classshark_1_1_p_c_a.html#ad3b450f29c9b4b265f0d16039cac8735">shark::PCA</a></li>
<li>penalize()&#160;:&#160;<a class="el" href="structshark_1_1_penalizing_evaluator.html#a20c4f924cbeb69a809ec865408662a08">shark::PenalizingEvaluator</a></li>
<li>penalizedFitness()&#160;:&#160;<a class="el" href="classshark_1_1_individual.html#a62d3d29935d144352503f3002bd93363">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a></li>
<li>PenalizingEvaluator()&#160;:&#160;<a class="el" href="structshark_1_1_penalizing_evaluator.html#ac563c794272c3d7a73f2d55a7e3ae2c0">shark::PenalizingEvaluator</a></li>
<li>Perceptron()&#160;:&#160;<a class="el" href="classshark_1_1_perceptron.html#a04743d83dcca06bc90dfc6ce793b29f1">shark::Perceptron&lt; InputType &gt;</a></li>
<li>permutation()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#aa4d7bdfee487c84a8a3eea33a4848fd7">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_boxed_s_v_m_problem.html#a7f91836f0eec0c624f00c7bd88c13b1f">shark::BoxedSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_c_s_v_m_problem.html#acaa712b9668b0d27820b0fb274e76d10">shark::CSVMProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_general_quadratic_problem.html#a6825de8bb886daad689839d3c7986713">shark::GeneralQuadraticProblem&lt; MatrixT &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#aac1b3e0a3248593ed5b917940ea8625f">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>phi()&#160;:&#160;<a class="el" href="classshark_1_1_binary_layer.html#ae5905132b4f335a2c8f795d026dfc8b9">shark::BinaryLayer</a>, <a class="el" href="classshark_1_1_bipolar_layer.html#a2e5d0f3116e5113176bc157c099606fa">shark::BipolarLayer</a>, <a class="el" href="classshark_1_1_gaussian_layer.html#ab7e9bdbf26ccea6190311b81ee4741cb">shark::GaussianLayer</a></li>
<li>point&#160;:&#160;<a class="el" href="classshark_1_1_evaluation_archive_1_1_point_result_pair_type.html#aea3786429ceb5ad051756fb5e5e850ec">shark::EvaluationArchive&lt; PointType, ResultT &gt;::PointResultPairType</a>, <a class="el" href="structshark_1_1_hypervolume_contribution_approximator_1_1_point.html#a359c315fa6267c52c26e2f8c38ed683a">shark::HypervolumeContributionApproximator::Point&lt; VectorType &gt;</a></li>
<li>Point()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_contribution_approximator_1_1_point.html#ad816e86a38c7e0c3dc7d36aa0bf139b1">shark::HypervolumeContributionApproximator::Point&lt; VectorType &gt;</a></li>
<li>point&#160;:&#160;<a class="el" href="structshark_1_1_result_set.html#a5afb306cbdabb9ddb962eb22dbf79bb6">shark::ResultSet&lt; SearchPointT, ResultT &gt;</a></li>
<li>PointerType&#160;:&#160;<a class="el" href="classshark_1_1_example_modified_kernel_matrix.html#aee5f5afe285add5ec8fe31eeba21731a">shark::ExampleModifiedKernelMatrix&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_kernel_matrix.html#a75fa1e1c877b9f52b7934e7fe4905ddd">shark::GaussianKernelMatrix&lt; T, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_matrix.html#ab4e409d88bff0f586ad51d92b04efc24">shark::KernelMatrix&lt; InputType, CacheType &gt;</a></li>
<li>PointResultPairConstIterator&#160;:&#160;<a class="el" href="classshark_1_1_evaluation_archive.html#a84a9cee45c1e863aec1da7bf24870a14">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></li>
<li>PointResultPairContainer&#160;:&#160;<a class="el" href="classshark_1_1_evaluation_archive.html#a4daf431052767cb6d8e85e46eeeceb5d">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></li>
<li>PointResultPairIterator&#160;:&#160;<a class="el" href="classshark_1_1_evaluation_archive.html#a86b696018a50ef61a414de27468017fb">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></li>
<li>PointResultPairType()&#160;:&#160;<a class="el" href="classshark_1_1_evaluation_archive_1_1_point_result_pair_type.html#a5b8713c854938ec683b6a529b76dbcab">shark::EvaluationArchive&lt; PointType, ResultT &gt;::PointResultPairType</a></li>
<li>PointSearch()&#160;:&#160;<a class="el" href="classshark_1_1_point_search.html#a8ae721d0d9d38babed22d1c81525c27a">shark::PointSearch</a></li>
<li>PointSetKernel()&#160;:&#160;<a class="el" href="classshark_1_1_point_set_kernel.html#aacab68230104cfe226d522632b42082c">shark::PointSetKernel&lt; InputType &gt;</a></li>
<li>PolynomialKernel()&#160;:&#160;<a class="el" href="classshark_1_1_polynomial_kernel.html#a94c0a51488a514cccc7db38afce0cbe8">shark::PolynomialKernel&lt; InputType &gt;</a></li>
<li>PolynomialMutator()&#160;:&#160;<a class="el" href="structshark_1_1_polynomial_mutator.html#a0210f6d7ca9e3f3e278ad6d0b80f8648">shark::PolynomialMutator</a></li>
<li>PoolingLayer()&#160;:&#160;<a class="el" href="classshark_1_1_pooling_layer.html#a3ec26ad400b96e72deb1193cf0ded646">shark::PoolingLayer&lt; VectorType &gt;</a></li>
<li>PopulationBased&#160;:&#160;<a class="el" href="classshark_1_1_indicator_based_m_o_c_m_a.html#ab3927aff6ee32e5c8cd7532aea7f7328aa6905c75b376e3713316c02701de72aa">shark::IndicatorBasedMOCMA&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_indicator_based_steady_state_m_o_c_m_a.html#a1c098d9a05f6242d35855b8975ae0262a3d451a21b0fcd70b3158d0dbe50225f1">shark::IndicatorBasedSteadyStateMOCMA&lt; Indicator &gt;</a></li>
<li>PopulationBasedStepSizeAdaptation()&#160;:&#160;<a class="el" href="classshark_1_1_population_based_step_size_adaptation.html#a639fa5d70bd1c62301f305243a5f2f37">shark::PopulationBasedStepSizeAdaptation</a></li>
<li>populationPartition()&#160;:&#160;<a class="el" href="structshark_1_1_reference_vector_guided_selection.html#a5baaad83af9cfd6838db277c4ad41a84">shark::ReferenceVectorGuidedSelection&lt; IndividualType &gt;</a></li>
<li>populationSize()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#aaa8990eaf10820245651f85d811f8b6b">shark::CrossEntropyMethod</a></li>
<li>positionInBatch()&#160;:&#160;<a class="el" href="classshark_1_1_data_view.html#a892be77ecf008f78e44452b1a201980a">shark::DataView&lt; DatasetType &gt;</a></li>
<li>precision()&#160;:&#160;<a class="el" href="classshark_1_1_regularization_network_trainer.html#a87ce3df17f42b18767bcb593dfbf2ac6">shark::RegularizationNetworkTrainer&lt; InputType &gt;</a></li>
<li>PrecomputedBlockMatrixType&#160;:&#160;<a class="el" href="classshark_1_1_epsilon_svm_trainer.html#aefaf6c666566d00fcd2822f6e3e34f46">shark::EpsilonSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>PrecomputedMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_precomputed_matrix.html#abea0cbaf28e2260105a01e2d1bac9098">shark::PrecomputedMatrix&lt; Matrix &gt;</a></li>
<li>PrecomputedMatrixType&#160;:&#160;<a class="el" href="classshark_1_1_one_class_svm_trainer.html#a86883b114a933da1c1ad6799f692da12">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_squared_hinge_c_svm_trainer.html#a9fe861ad7ccd5a4f2d89732f010c26c4">shark::SquaredHingeCSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>precomputeHidden()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#a119948b017a9d29cdf5f10e20f4ed556">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>precomputeKernel()&#160;:&#160;<a class="el" href="classshark_1_1_qp_config.html#ae90c5c93fc02fad6fc07ca6b04fc78cc">shark::QpConfig</a></li>
<li>precomputeVisible()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#a196f8674930d1d17709900801f48243d">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>PreferedSelectionStrategy&#160;:&#160;<a class="el" href="structshark_1_1_box_based_shrinking_strategy.html#a8e49b05f112110b820b466c39ac9042e">shark::BoxBasedShrinkingStrategy&lt; Problem &gt;</a>, <a class="el" href="classshark_1_1_box_constrained_problem.html#a9a09c817b94eb35a5b80ecf647149b95">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#acef7c20b210e81a62d01e9eadd61dc49">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>preInitializationMethod&#160;:&#160;<a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#ab2bbffc9336fbe61c3b667f8f3f0672e">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>probabilities()&#160;:&#160;<a class="el" href="classshark_1_1_multi_nomial_distribution.html#a16f80a1746538bcddf35222aba064f00">shark::MultiNomialDistribution</a></li>
<li>ProductKernel()&#160;:&#160;<a class="el" href="classshark_1_1_product_kernel.html#a7b82db04cf4a0e7945161e332204fe34">shark::ProductKernel&lt; InputType &gt;</a></li>
<li>ProjectBudgetMaintenanceStrategy()&#160;:&#160;<a class="el" href="classshark_1_1_project_budget_maintenance_strategy.html#aeb21c7cad1d543eb5e492b76db1dc659">shark::ProjectBudgetMaintenanceStrategy&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_project_budget_maintenance_strategy_3_01_real_vector_01_4.html#a53e3bfad62d2c2e4d74ccfccfb9faae2">shark::ProjectBudgetMaintenanceStrategy&lt; RealVector &gt;</a></li>
<li>proposeStartingPoint()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#acd2922036a6388fde1173490079bb22b">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a>, <a class="el" href="structshark_1_1benchmarks_1_1_ackley.html#a0c9e13f0da191fcf2a83988ff5680096">shark::benchmarks::Ackley</a>, <a class="el" href="structshark_1_1benchmarks_1_1_cigar.html#aecd195b4f90a5db49e588f1f42602daa">shark::benchmarks::Cigar</a>, <a class="el" href="classshark_1_1benchmarks_1_1_cigar_discus.html#acb893e78074c47fb828f92c7ce3d4c08">shark::benchmarks::CigarDiscus</a>, <a class="el" href="structshark_1_1benchmarks_1_1_c_i_g_t_a_b1.html#a6111aa5a41a5c9f602df42e248789d5e">shark::benchmarks::CIGTAB1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_c_i_g_t_a_b2.html#a211035af2383fc2e8de1e345932dae0e">shark::benchmarks::CIGTAB2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_constrained_sphere.html#a200e3ee72e9f1bb9071b29c1fa10bdad">shark::benchmarks::ConstrainedSphere</a>, <a class="el" href="structshark_1_1benchmarks_1_1_diff_powers.html#a02f3f01a3022c8c7ad0c3008f8080f89">shark::benchmarks::DiffPowers</a>, <a class="el" href="structshark_1_1benchmarks_1_1_discus.html#af9860568c22beffca9fc5f2bcea8d88d">shark::benchmarks::Discus</a>, <a class="el" href="structshark_1_1benchmarks_1_1_e_l_l_i1.html#a6076013de21bd58a9ae061425ea8a2e2">shark::benchmarks::ELLI1</a>, <a class="el" href="structshark_1_1benchmarks_1_1_e_l_l_i2.html#a4309b3cf58d96223d42cd9087bbba6c6">shark::benchmarks::ELLI2</a>, <a class="el" href="structshark_1_1benchmarks_1_1_ellipsoid.html#a8e57d7bff2a231ce93eb809fb08f6382">shark::benchmarks::Ellipsoid</a>, <a class="el" href="structshark_1_1benchmarks_1_1_himmelblau.html#ab023c0be9b7d3f291df132f0f315c0d8">shark::benchmarks::Himmelblau</a>, <a class="el" href="classshark_1_1benchmarks_1_1_markov_pole.html#a88421faf6dfd7200e9050c69de46ba47">shark::benchmarks::MarkovPole&lt; HiddenNeuron, OutputNeuron &gt;</a>, <a class="el" href="classshark_1_1benchmarks_1_1_multi_objective_benchmark.html#a85f5750d889d29fd9cffaa3406a8a166">shark::benchmarks::MultiObjectiveBenchmark&lt; Objectives &gt;</a>, <a class="el" href="classshark_1_1benchmarks_1_1_non_markov_pole.html#a1476a34b5e8086c8e5d2a1eea5270d59">shark::benchmarks::NonMarkovPole</a>, <a class="el" href="structshark_1_1benchmarks_1_1_rosenbrock.html#ab58f55f1cc973e170f132b1e193fa131">shark::benchmarks::Rosenbrock</a>, <a class="el" href="structshark_1_1benchmarks_1_1_rotated_objective_function.html#ac45c8de9fc95df81191d2bf766193abb">shark::benchmarks::RotatedObjectiveFunction</a>, <a class="el" href="structshark_1_1benchmarks_1_1_schwefel.html#aad3a4189844043269e946af7c43a3a18">shark::benchmarks::Schwefel</a>, <a class="el" href="structshark_1_1benchmarks_1_1_sphere.html#abf22976a98b7e31e9f97945c2c7550c5">shark::benchmarks::Sphere</a>, <a class="el" href="classshark_1_1_contrastive_divergence.html#ac24476a87828b2d74f9da679e8d06b57">shark::ContrastiveDivergence&lt; Operator &gt;</a>, <a class="el" href="classshark_1_1_error_function.html#addeffd025bf0521615ba91883451a690">shark::ErrorFunction&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_evaluation_archive.html#a997a476a3869a1b8794133606aec94b4">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1_exact_gradient.html#a4ca798c77e7b1cf431b8459b1358b8d5">shark::ExactGradient&lt; RBMType &gt;</a>, <a class="el" href="classshark_1_1_kernel_target_alignment.html#a5743503781d8d4c9ea42164e0662a281">shark::KernelTargetAlignment&lt; InputType, LabelType &gt;</a>, <a class="el" href="classshark_1_1_multi_chain_approximator.html#a2ff87fa005fe8314dca5a49c8675adf5">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_negative_log_likelihood.html#a06c546fd3e801511f22028e776eaf981">shark::NegativeLogLikelihood</a>, <a class="el" href="classshark_1_1_single_chain_approximator.html#aa02497017d33d8929b7a8a21f7baf6b4">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_variational_autoencoder_error.html#a5e6dd6b42efb979395d221900550c7bb">shark::VariationalAutoencoderError&lt; SearchPointType &gt;</a></li>
<li>ProxyIterator&#160;:&#160;<a class="el" href="classshark_1_1_proxy_iterator.html#aa6a1bbfb0c569f7a36652f00eb5c60c6">shark::ProxyIterator&lt; Sequence, ValueType, Reference &gt;</a></li>
<li>push_back()&#160;:&#160;<a class="el" href="group__shark__globals.html#gadbf9ee4b9fcc8d6ae46467b3fd7721ad">shark::Data&lt; Type &gt;</a>, <a class="el" href="group__shark__globals.html#ga5b3eb1f239a148b1f9b004b12150fddd">shark::LabeledData&lt; InputT, LabelT &gt;</a></li>
</ul>
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